Patient-derived models of acquired resistance can identify effective drug combinations for cancer
Open accessAbstract
Targeted cancer therapies have produced substantial clinical responses, but most tumors develop resistance to these drugs. Here, we describe a pharmacogenomic platform that facilitates rapid discovery of drug combinations that can overcome resistance. We established cell culture models derived from biopsy samples of lung cancer patients whose disease had progressed while on treatment with epidermal growth factor receptor (EGFR) or anaplastic lymphoma kinase (ALK) tyrosine kinase inhibitors and then subjected these cells to genetic analyses and a pharmacological screen. Multiple effective drug combinations were identified. For example, the combination of ALK and MAPK kinase (MEK) inhibitors was active in an ALK -positive resistant tumor that had developed a MAP2K1 activating mutation, and the combination of EGFR and fibroblast growth factor receptor (FGFR) inhibitors was active in an EGFR mutant resistant cancer with a mutation in FGFR3 . Combined ALK and SRC (pp60c-src) inhibition was effective in several ALK-driven patient-derived models, a result not predicted by genetic analysis alone. With further refinements, this strategy could help direct therapeutic choices for individual patients.
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Existing cancer cell growth platforms such as ATP-based assays require extended culture and large numbers of tumor cells.
“Existing platforms to measure cancer cell growth, such as ATP-based assays (CellTiter-Glo), require extended time in culture and a large number of tumor cells10.”
From Drug sensitivity of single cancer cells is predicted by changes in mass accumulation rate (2016) · cites this paper as [10]
Bulk growth assays are poorly suited for characterizing therapeutic susceptibility of subpopulations within heterogeneous tumors.
“Furthermore, these bulk approaches are ill-suited for characterizing therapeutic susceptibility of subpopulations that exist within heterogeneous tumors10.”
From Drug sensitivity of single cancer cells is predicted by changes in mass accumulation rate (2016) · cites this paper as [10]
Crystal et al. used standard proliferation assays to measure drug susceptibility in bulk PDCL cultures.
“For example, Crystal et al. applied standard proliferation-based assays to quantify therapeutic susceptibilities of bulk cultures of PDCLs10.”
From Drug sensitivity of single cancer cells is predicted by changes in mass accumulation rate (2016) · cites this paper as [10]
Crystal et al.'s ex vivo screening results predicted in vivo xenograft responses to combination treatments.
“The results from their ex vivo screening predicted the response of in vivo xenografts to combination therapies.”
From Drug sensitivity of single cancer cells is predicted by changes in mass accumulation rate (2016) · cites this paper as [10]
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- Authors
- Crystal, A. S., Shaw, A. T., Sequist, L. V., Friboulet, L., Niederst, M. J., Lockerman, E. L., Frias, R. L., Gainor, J. F., Amzallag, A., Greninger, P., Lee, D., Kalsy, A., Gomez-Caraballo, M., Elamine, L., Howe, E., Hur, W., Lifshits, E., Robinson, H. E., Katayama, R., Faber, A. C., Awad, M. M., Ramaswamy, S., Mino-Kenudson, M., Iafrate, A. J., Benes, C. H., & Engelman, J. A.
- Affiliations
- Harvard University (US)
- Massachusetts General Hospital Cancer Center, Department of Medicine and Harvard Medical School, Boston, MA 02114, USA.
- Corresponding author
- Benes, Cyril H.
- Engelman, Jeffrey A.
- ORCID
- Venue
- Science
- Published
- 2014-12-19
- Volume
- 346
- Issue
- 6216
- Pages
- 1480-1486
- ISSN
- 0036-8075 (ISSN-L)
- 1095-9203
- PMC
- PMC4388482
- OpenAlex
- W1969391810
- Cited by
- 708
- References
- 35
- Citations by year
- 2026: 10 · 2025: 30 · 2024: 33 · 2023: 55 · 2022: 52 · 2021: 70 · 2020: 62 · 2019: 75 · 2018: 72 · 2017: 81 · 2016: 85 · 2015: 77 · 2014: 5
- FWCI
- 66.19
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Science (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- Wellcome Trust (086357, 102696)
- National Institutes of Health (5u54hg006097-03)
- Japan Society for the Promotion of Science (25710015)
- National Human Genome Research Institute (1U54HG006097-01, U54-HG006097)
- National Cancer Institute (P50CA090578, R01CA164273, R01CA137008)
- Topics
- Health Sciences › Medicine › Pulmonary and Respiratory Medicine › Lung Cancer Treatments and Mutations
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Cancer Genomics and Diagnostics
- Health Sciences › Medicine › Oncology › HER2/EGFR in Cancer Research
- Keywords
- acquired drug resistance, patient-derived tumor models, drug combination discovery, lung cancer, EGFR tyrosine kinase inhibitors, ALK inhibitors, MEK inhibitors, MAP2K1 mutation, FGFR3 mutation, Src kinase inhibition, pharmacogenomics, targeted cancer therapy
- MeSH terms
- Anaplastic Lymphoma Kinase, Antineoplastic Combined Chemotherapy Protocols, Carcinoma, Non-Small-Cell Lung, DNA Mutational Analysis, Drug Screening Assays, Antitumor, Enzyme Activation, Humans, Lung Neoplasms, Mutation, Pyrimidines, Sulfones, Tumor Cells, Cultured, Proto-Oncogene Proteins pp60(c-src), Drug Resistance, Neoplasm, Receptor Protein-Tyrosine Kinases, Protein Kinase Inhibitors, MAP Kinase Kinase 1, Receptor, Fibroblast Growth Factor, Type 3, Molecular Targeted Therapy, Patient-Specific Modeling, ErbB Receptors
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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